N: 1147
N: 285
N: 226
IND MLW UK
BS1 289 81 59
BS2 287 75 59
BS3 289 68 53
BS5 282 61 55
Shannon Richness
MLW-IND 0.0000 0.0000
UK-IND 0.2262 0.4374
UK-MLW 0.0300 0.0000
Shannon Richness
India (OPV)-India (IPV) 0.4652 0.3768
Shannon Richness
MLW-IND 0.0001 0.0000
UK-IND 0.4844 0.6809
UK-MLW 0.0002 0.0000
Shannon Richness
MLW-IND 0.0002 0.0000
UK-IND 0.0661 0.1164
UK-MLW 0.4646 0.0488
Shannon Richness
MLW-IND 0.2354 0.0000
UK-IND 0.2310 0.0503
UK-MLW 0.9894 0.2179
Shannon Richness
MLW-IND 0.1013 0.0001
UK-IND 0.2347 0.4217
UK-MLW 0.9614 0.0690
Shannon Richness
MLW-IND 0.9997 0.0625
UK-IND 0.0002 0.0002
UK-MLW 0.0026 0.0000
Shannon Richness
1 0.6225 0.7129
India Malawi UK
BS1 289 81 59
BS2 287 75 59
BS3 289 68 53
BS5 282 61 55
MS1 288 83 57
Permutation: free
Number of permutations: 999
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
family_ID 473 146.38 0.309479 3.4394 0.57877 0.001 ***
Residuals 1184 106.54 0.089982 0.42123
Total 1657 252.92 1.00000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
week R2 p n
1 week of life 1 0.08963047 0.001 429
2 week of life 4 0.07156166 0.001 421
3 week of life 6 0.06425047 0.001 410
4 week of life 10 0.06603234 0.001 398
5 mother 0.16414628 0.001 428
Permutation: free
Number of permutations: 999
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
family_ID 473 204.66 0.43268 2.895 0.5363 0.001 ***
Residuals 1184 176.96 0.14946 0.4637
Total 1657 381.61 1.0000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
week R2 p n
1 week of life 1 0.09855442 0.001 429
2 week of life 4 0.10665922 0.001 421
3 week of life 6 0.08819497 0.001 410
4 week of life 10 0.11127149 0.001 398
5 mother 0.17832746 0.001 428
Longitudinal samples from a given infant more closely clustered than expected by chance in each of the three cohorts.
Number of genera tested: 31
Number of discriminant genera (FDR p < 0.05): 20 (India = 10; UK = 10) Failed to converge: 0
Number of genera tested: 43
Number of discriminant genera (FDR p < 0.05): 22 (India = 6; Malawi = 16) Failed to converge: 0
Number of genera tested: 45
Number of discriminant genera (FDR p < 0.05): 29 (Malawi = 22; UK = 7) Failed to converge: 0
R version 3.6.1 (2019-07-05)
Platform: x86_64-apple-darwin15.6.0 (64-bit)
Running under: macOS 10.16
Matrix products: default
BLAS: /Library/Frameworks/R.framework/Versions/3.6/Resources/lib/libRblas.0.dylib
LAPACK: /Library/Frameworks/R.framework/Versions/3.6/Resources/lib/libRlapack.dylib
locale:
[1] en_GB.UTF-8/en_GB.UTF-8/en_GB.UTF-8/C/en_GB.UTF-8/en_GB.UTF-8
attached base packages:
[1] parallel stats4 stats graphics grDevices utils datasets
[8] methods base
other attached packages:
[1] FSA_0.9.0 ALDEx2_1.18.0
[3] sjstats_0.18.0 ggExtra_0.9
[5] formattable_0.2.0.1 NBZIMM_1.0
[7] inlmisc_0.5.2 decontam_1.6.0
[9] ggtree_2.0.4 wesanderson_0.3.6
[11] phangorn_2.5.5 ape_5.4-1
[13] DECIPHER_2.14.0 RSQLite_2.2.1
[15] Biostrings_2.54.0 XVector_0.26.0
[17] cowplot_1.1.0 scales_1.1.1
[19] RVAideMemoire_0.9-78 DescTools_0.99.38
[21] ggsignif_0.6.0 binom_1.1-1
[23] shiny_1.5.0 randomcoloR_1.1.0.1
[25] DESeq2_1.26.0 SummarizedExperiment_1.16.1
[27] DelayedArray_0.12.3 BiocParallel_1.20.1
[29] Biobase_2.46.0 GenomicRanges_1.38.0
[31] GenomeInfoDb_1.22.1 IRanges_2.20.2
[33] S4Vectors_0.24.4 BiocGenerics_0.32.0
[35] crossval_1.0.3 UpSetR_1.4.0
[37] labdsv_2.0-1 mgcv_1.8-33
[39] nlme_3.1-149 ggpubr_0.4.0
[41] data.table_1.12.8 corrplot_0.84
[43] ZIBR_0.1 vegan_2.5-6
[45] lattice_0.20-41 permute_0.9-5
[47] randomForest_4.6-14 matrixStats_0.57.0
[49] lme4_1.1-23 Matrix_1.2-18
[51] reshape2_1.4.4 pheatmap_1.0.12
[53] DT_0.16 plotly_4.9.3
[55] cluster_2.1.0 tidyr_1.1.2
[57] dplyr_1.0.2 magrittr_1.5
[59] plyr_1.8.6 kableExtra_1.2.1
[61] gridExtra_2.3 RColorBrewer_1.1-2
[63] knitr_1.30 ggplot2_3.3.2
[65] phyloseq_1.30.0
loaded via a namespace (and not attached):
[1] estimability_1.3 coda_0.19-4 bit64_4.0.5
[4] rpart_4.1-15 RCurl_1.98-1.2 generics_0.0.2
[7] bit_4.0.4 webshot_0.5.2 xml2_1.3.2
[10] httpuv_1.5.4 xfun_0.18 hms_0.5.3
[13] evaluate_0.14 promises_1.1.1 readxl_1.3.1
[16] igraph_1.2.6 DBI_1.1.0 geneplotter_1.64.0
[19] htmlwidgets_1.5.3 purrr_0.3.4 ellipsis_0.3.1
[22] backports_1.1.10 V8_3.2.0 insight_0.9.6
[25] annotate_1.64.0 vctrs_0.3.4 sjlabelled_1.1.7
[28] abind_1.4-5 withr_2.3.0 checkmate_2.0.0
[31] rgdal_1.5-18 emmeans_1.5.1 treeio_1.10.0
[34] lazyeval_0.2.2 crayon_1.3.4 flexdashboard_0.5.2
[37] genefilter_1.68.0 labeling_0.3 pkgconfig_2.0.3
[40] nnet_7.3-14 rlang_0.4.8 lifecycle_0.2.0
[43] miniUI_0.1.1.1 modelr_0.1.8 cellranger_1.1.0
[46] raster_3.3-13 carData_3.0-4 Rhdf5lib_1.8.0
[49] boot_1.3-25 base64enc_0.1-3 png_0.1-7
[52] viridisLite_0.3.0 parameters_0.8.6 rootSolve_1.8.2.1
[55] bitops_1.0-6 blob_1.2.1 stringr_1.4.0
[58] jpeg_0.1-8.1 rstatix_0.6.0 memoise_1.1.0
[61] zlibbioc_1.32.0 compiler_3.6.1 ade4_1.7-15
[64] htmlTable_2.1.0 Formula_1.2-4 MASS_7.3-53
[67] tidyselect_1.1.0 stringi_1.5.3 forcats_0.5.0
[70] yaml_2.2.1 locfit_1.5-9.4 latticeExtra_0.6-29
[73] grid_3.6.1 fastmatch_1.1-0 tools_3.6.1
[76] lmom_2.8 rio_0.5.16 rstudioapi_0.11
[79] foreach_1.5.1 foreign_0.8-71 gld_2.6.2
[82] farver_2.0.3 Rtsne_0.15 digest_0.6.25
[85] rvcheck_0.1.8 BiocManager_1.30.10 quadprog_1.5-8
[88] Rcpp_1.0.5 car_3.0-10 broom_0.7.1
[91] performance_0.5.0 later_1.1.0.1 httr_1.4.2
[94] AnnotationDbi_1.48.0 effectsize_0.3.3 colorspace_1.4-1
[97] rvest_0.3.6 XML_3.99-0.3 splines_3.6.1
[100] statmod_1.4.34 tidytree_0.3.3 expm_0.999-5
[103] sp_1.4-4 multtest_2.42.0 Exact_2.1
[106] xtable_1.8-4 jsonlite_1.7.1 nloptr_1.2.2.2
[109] R6_2.4.1 Hmisc_4.4-1 pillar_1.4.6
[112] htmltools_0.5.0 mime_0.9 glue_1.4.2
[115] fastmap_1.0.1 minqa_1.2.4 class_7.3-17
[118] codetools_0.2-17 mvtnorm_1.1-1 tibble_3.0.4
[121] curl_4.3 zip_2.1.1 openxlsx_4.2.2
[124] survival_3.2-7 rmarkdown_2.4 biomformat_1.14.0
[127] munsell_0.5.0 e1071_1.7-4 rhdf5_2.30.1
[130] GenomeInfoDbData_1.2.2 iterators_1.0.13 sjmisc_2.8.5
[133] haven_2.3.1 gtable_0.3.0 bayestestR_0.7.2
.